The invention relates to a receiving method for use in a telecommunication system in which a number of signal components are detected simultaneously from a received signal.
One central problem in the design and implementation of telecommunication systems is simultaneous transmission of signals to and reception of signals from several simultaneous users such that interference between the signals is minimal. Because of this problem and the transmission capacity used, various transmission protocols and multiple access methods have been developed, the most common in mobile phone communication being FDMA and TDMA methods, and recently the CDMA method also.
CDMA is a multiple access method based on a spread spectrum technique, and it has recently been put into use in cellular radio systems in addition to previously used FDMA and TDMA. CDMA has many advantages over the prior methods, such as simplicity of frequency planning, and spectrum efficiency.
In the CDMA method, a narrow-band data signal of a user is multiplied to a relatively broad band by a spreading code having a much broader band than the data signal. Band widths used in known test systems include, e.g., 1.25 MHz, 10 MHz and 25 MHz. During the multiplication, the data signal spreads over the entire band to be used. All the users transmit simultaneously on the same frequency band. On each connection between a base station and a mobile station, a different spreading code is used, and the signals of the users can be distinguished from one another in the receivers on the basis of the user's spreading code. If possible, the spreading codes are selected in such a way that they are mutually orthogonal, i.e. they do not correlate with one another.
Correlators in conventionally implemented CDMA receivers are synchronized with a desired signal, which they recognize on the basis of the spreading code. In the receiver, the data signal is restored to the original band by multiplying it by the same spreading code as in the transmission step. Ideally, the signals that have been multiplied by some other spreading code do not correlate and are not restored to the narrow band. In view of the desired signal, they thus appear as noise. The object is thus to detect the signal of the desired user from among a number of interfering signals. In practice, the spreading codes partially correlate, and the signals of the other users make it more difficult to detect the desired signal since they distort the received signal non-linearly. This interference caused by the users to one another is called multiple access interference.
In a telecommunication system applying the TDMA multiple access method, there are several frequencies in use, each frequency being divided into time slots, in which the signals of different users are inserted. Each user thus has a time slot of their own. Since the frequency range reserved for the system is usually limited, the frequencies used must usually be repeated in cells located within a certain distance. For high frequency efficiency, the distance must be kept as short as possible. As a result, different transmissions at the same frequencies interfere with one another. In a certain time slot, a noise signal is thus also heard in the receiver in addition to the desired signal, the noise signal coming from some other connection using the same frequency.
The single-user detection method described above in connection with CDMA is not optimal, since the information contained in the signals of the other users is not taken into account in the detection. In addition, non-linearities caused by partly non-orthogonal spreading codes and distortion of the signal over the radio path cannot be corrected by a conventional detection method. In an optimal receiver, all information contained in the signals of the users is taken into account so that the signals can be optimally detected using, e.g., a Viterbi algorithm. The advantage of this detection method, e.g. in a CDMA system is that the bit error ratio curves of the receiver are similar to a situation in a single-user CDMA system where no multiple access interference occurs. For example, a near-far problem, which is typical of CDMA systems, does not arise. A near-far problem is a situation where the transmission from a transmitter close to the receiver blankets the more distant transmitters. The major drawback of the Viterbi algorithm is that the computing efficiency that it requires increases exponentially with the number of users. For example, with QPSK modulation, a ten-user system with a bit rate of 100 kbit/s would require 105 million operations per second for computing a probability function. In practice, this makes it impossible to implement an optimal receiver.
An optimal receiver, however, can be approximated by different methods. Prior art teaches various methods for simultaneous multiuser detection (MUD). The best known methods of this kind are linear multiuser detection, a decorrelating detector and a multistage detector. These methods are described in greater detail in Varanasi, Aazhang, `Multistage detection for asynchronous code division multiple access communications,` IEEE Transactions on Communications, Vol. 38, pp. 509-519, April 1990; Lupas, Verdu, `Linear multiuser detectors for synchronous code-division multiple access channels,` IEEE Transactions on Information Theory, Vol. 35, No. 1, pp. 123-136, January 1989; and Lupas, Verdu, `Near-far resistance of multiuser detectors in asynchronous channels,` IEEE Transactions on Communications, Vol. 38, April 1990. The disadvantage of all these methods, however, is that they do not track changes on the radio channel.
In the detection of a multiuser signal, it is previously known to use an adaptive signal dot matrix which tracks changes on the channel. The method is described in international patent application PCT/FI94/00503, which is incorporated herein by reference. The disadvantage of the method, however, is that as the number of simultaneous users increases, the computing capacity needed increases exponentially.
Further, international patent application PCT/US93/01154 teaches recursive estimation of changes on a radio channel, but the method is restricted to computation of weighting coefficients of the signals, which are useful in the detection of a single-user signal.